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Evolutionary virus immune strategy for temporal networks based on community vitality

Version 2 2024-06-06, 06:32
Version 1 2017-04-06, 13:00
journal contribution
posted on 2024-06-06, 06:32 authored by M Li, C Fu, XY Liu, J Yang, T Zhu, L Han
Preventing viruses spreading in networks is a hot topic. Existing immune strategies are mainly designed for static networks, which become ineffective for temporal networks. In this paper, we propose an evolutionary virus immune strategy for temporal networks, which takes into account the community evolution. First, we define a new metric, community vitality (CV), to quantize the evolution characteristics of communities. Second, based on the community vitality, we propose an immune strategy which selects an optimized number of initial nodes according to node influence (NI). Third, a theoretical analysis is proposed to measure the immune effect of the evolutionary immune strategy. Compared with the random immunization, the targeted immunization and the acquaintance immune strategy, we show that the proposed strategy has a much larger coverage, i.e., more nodes will have immune ability given the same number of initial immune nodes.

History

Journal

Future generation computer systems

Volume

74

Pagination

276-290

Location

Amsterdam, The Netherlands

ISSN

0167-739X

Language

eng

Publication classification

C Journal article, C1 Refereed article in a scholarly journal

Copyright notice

2016, Elsevier

Publisher

Elsevier